Triple
T1698756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Reading |
E36719
|
entity |
| Predicate | typeOfBishop |
P31297
|
FINISHED |
| Object | suffragan bishop |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: suffragan bishop | Statement: [Bishop of Reading, typeOfBishop, suffragan bishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBishop Context triple: [Bishop of Reading, typeOfBishop, suffragan bishop]
-
A.
hasBishop
Indicates that one entity possesses, is assigned, or is associated with a bishop in relation to another entity.
-
B.
hasNumberOfBishops
Indicates the relationship that specifies how many bishops are associated with a given entity.
-
C.
typeOfSaint
Indicates that one entity is classified as a specific kind or category of saint in relation to another entity.
-
D.
currentBishop
Indicates that one entity currently holds the position or role of bishop with respect to another entity (such as a diocese or church).
-
E.
majorityOfBishopsFrom
Indicates that, within a given group or context, more than half of the bishops originate from or are associated with a specified place or source.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf169da888190b3aa334752f1952b |
completed | March 6, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69aa61b8ce348190b46154af0b041ff0 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aaf16865488190a76577b36760dc7a |
completed | March 6, 2026, 3:23 p.m. |
Created at: March 4, 2026, 7:30 p.m.